Agentic AI Engineer

Infosys•Raleigh, CT

6d•Hybrid

About The Position

Infosys Topaz is an AI-first suite of services, solutions, and platforms designed to accelerate business value through generative AI technologies. It amplifies the potential of individuals, enterprises, and communities by fostering unprecedented innovations, pervasive efficiencies, and connected ecosystems. Leveraging Infosys' applied AI framework, Topaz empowers users to deliver cognitive solutions that drive growth, build interconnected ecosystems, and unlock efficiencies at scale. Join us to be part of a pioneering team at the forefront of AI innovation. At Infosys Topaz, you'll have the opportunity to work with cutting-edge technologies, collaborate with industry experts, and contribute to transformative projects that shape the future of business. We are committed to fostering a culture of continuous learning and growth, ensuring that our team members thrive in a dynamic and supportive environment. If you're passionate about AI and eager to make a significant impact, Infosys Topaz is the perfect place for you to grow and excel.

Requirements

Experience in designing, developing, and deploying Gen AI applications using LLMs and agentic frameworks (e.g., LangGraph, AutoGen, Crew AI).
Experience in software engineering or data science, with 2–3 years in Gen AI or LLM-based systems.
Experience in Python programming skills and ML/AI libraries (Hugging Face Transformers, LangChain, PyTorch).
Hands-on experience with vector databases (FAISS, Pinecone, Weaviate, AI Search).
Prior experience in implementing LLMOps practices including prompt versioning, caching, observability, and cost tracking.
Experience in building and optimizing RAG pipelines with hybrid retrieval, semantic chunking, and vector search.
Bachelor’s degree or foreign equivalent required from an accredited institution. Will also consider three years of progressive experience in the specialty in lieu of every year of education.

Nice To Haves

Experience with REST API development (FastAPI, Flask) and containerization (Docker).
Experience with Fine-tune open-source and proprietary LLMs using techniques like LoRA, QLoRA, and PEFT.

Responsibilities

Contribute to the requirements elicitation process by documenting assigned parts of business requirements, in line with guidance provided
Facilitate software application design discussions, and document design decisions to guide the technical team towards building software solutions
Participate in coding and integrate new features or updates into existing applications, with a focus on maintaining system stability
Conduct code reviews, do changes to the codebase and maintain code repositories
Implement test strategies, analyse results, and coordinate bug fixes to uphold the software quality standards
Develop user training programs, documentation, and support frameworks to ensure a smooth transition to new software applications
Actively participate in resolving production issues and recommend preventive strategies to enhance system reliability
Maintain detailed records of code, testing techniques, and support activities to enrich the knowledge base and assist other similar projects